The boundedness of penalty parameters in an augmented Lagrangian method with constrained subproblems

Augmented Lagrangian methods are effective tools for solving large-scale nonlinear programming problems. At each outer iteration, a minimization subproblem with simple constraints, whose objective function depends on updated Lagrange multipliers and penalty parameters, is approximately solved. When...

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Bibliographic Details

Published in:	Optimization methods & software Vol. 27; no. 6; pp. 1001 - 1024
Main Authors:	Birgin, Ernesto G., Fernández, Damián, Martínez, J. M.
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 01.12.2012 Taylor & Francis Ltd
Subjects:	Algorithms augmented Lagrangian methods Computer programs Fines & penalties Lagrange multipliers Mathematical analysis Mathematical models Nonlinear programming numerical experiments Optimization penalty parameters Software Studies
ISSN:	1055-6788, 1029-4937
Online Access:	Get full text
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